Embedding networks.
For comparisons to SLADE, we employ ResNet50 [1]} with 512 embedding dimensions as the backbone network of the teacher and student models.
Before applying STML, these models are pre-trained either on ImageNet [2]} or by SwAV [3]}, then fine-tuned with the MS loss [4]} on a labeled dataset (i.e., CUB or Cars).
